Head of Data Transformation

Robert Vint; Amsterdam; Sur place; EUR 180 000 - 300 000; Plein temps

Résumé du poste

Robert Vint is seeking an experienced Data leader to define and drive a transformation that unifies data across the organisation. You will shape architecture, governance and operating models to enable AI-enabled decision making and scalable analytics.

You will work closely with the CEO and senior leaders to connect business strategy with data capabilities, establishing clear ownership and an organisation-wide data culture. This is a strategic role with practical transformation execution.

Qualifications

• Proven experience building enterprise-wide data foundations.
• Experience developing data strategies and governance frameworks.
• Strong understanding of data platforms, cloud architecture and data management.
• Ability to influence senior leaders and work with cross-functional teams.

Responsabilités

• Define and drive the roadmap for a unified data foundation across the organisation.
• Shape data architecture including platforms, integration, storage and accessibility.
• Drive data quality, governance, ownership and security.
• Translate business needs into data capabilities and priorities.
• Partner with CEO/CTO to align strategy with technology and organisational change.

Connaissances

Data strategy

Data architecture

Data governance

Stakeholder management

AI readiness

SQL and Python

Outils

Cloud platforms

ETL/ELT

Description du poste

For an international organisation, we are looking for an experienced Data leader who can build the foundation for an organisation-wide data transformation.

The organisation has significant data assets and ambitions to accelerate its use of analytics and AI. The next step is to bring these elements together: creating a robust, scalable and well-governed data foundation that enables the business to make better decisions, improve operations and unlock new opportunities through AI.

Working closely with the CEO, CTO and senior leadership, you will take ownership of the organisation's data transformation agenda. You will connect business strategy, data architecture, technology and organisational change, ensuring that the right foundations, capabilities and operating models are in place to support the organisation's ambitions.

This role combines strategic leadership with transformation execution. You will not simply oversee the data function; you will shape how data is structured, managed, accessed and used across the organisation.

What you will do

• Build the data foundation: Define and drive the roadmap towards a unified, scalable and reliable data foundation across the organisation.
• Shape data architecture: Establish the architectural direction for data platforms, integration, storage and accessibility, working closely with technology teams.
• Improve data quality and consistency: Drive common data definitions, standards, ownership and quality across different business units and systems.
• Establish data governance: Develop the governance framework covering data ownership, accountability, quality, security, privacy and responsible AI.
• Connect fragmented data environments: Bring together different data sources, platforms and business systems to create a more integrated and accessible data ecosystem.
• Translate business needs into data capabilities: Understand business challenges and translate them into data, analytics and technology priorities.
• Develop the operating model: Define how central data capabilities work together with individual business units, balancing common standards with local autonomy.
• Create AI readiness: Ensure the data foundation supports the responsible adoption and scaling of Generative and Agentic AI applications.
• Drive organisational adoption: Build data literacy and ensure that reliable data and insights become accessible and usable throughout the organisation.
• Deliver measurable transformation: Turn the data strategy into an actionable roadmap, prioritising investments and measuring progress through tangible business outcomes.

What you bring

• Proven experience building or transforming enterprise-wide data foundations in complex organisations.
• Experience developing and implementing data strategies, architecture and governance frameworks.
• Strong understanding of modern data platforms, cloud architecture, data integration, data quality and data management.
• Experience working across multiple business units, countries or decentralised organisations.
• The ability to connect business strategy and requirements with data architecture and technology decisions.
• Experience establishing data ownership, governance structures and operating models.
• Understanding of how a robust data foundation enables advanced analytics, automation and AI adoption.
• Strong stakeholder management skills, with the ability to influence the CEO, CTO and senior business leaders.
• A pragmatic transformation mindset, combining strategic thinking with the ability to drive implementation and organisational change.
• Technical understanding of SQL, Python, ETL/ELT, data warehousing and modern data platforms is an advantage.

The challenge

The organisation has data, technology and the ambition to do more with both. However, the underlying data landscape is still developing. Different business units have different systems, data maturity levels, processes and approaches to data management.

At the same time, the rapid development of AI is creating new opportunities, but also exposing the importance of having the right foundations in place.

Your challenge is to create those foundations and turn them into an organisation-wide capability.

You will need to establish a clear data architecture, improve data quality and accessibility, create ownership and governance, and bring different business units together around a common direction.

The objective is not simply to build another data platform or centralise everything. It is to create an integrated, reliable and scalable data ecosystem that allows the organisation to operate more intelligently, make better decisions and accelerate its use of AI.

Do you have the answers to the questions below:

How do you move from fragmented data environments towards a coherent data foundation?

How do you create common standards without restricting the autonomy of individual businesses?

And how do you ensure the organisation is ready to use data and AI at scale?